LOS ANGELES —
The rest was a giant math problem. The scientists wrote a computer program to sort through the patterns of brain activity captured by the functional MRI in both waking and sleeping states; then the program looked for links between those brain activity patterns and specific images.
The computers learned to decode dream imagery with an average accuracy of 60 percent, according to the study. In some cases, the accuracy was significantly higher.
“For some categories — like male, female and other characters — you can predict if this character was in the dream or not with an accuracy of 70 percent to75 percent,” said study leader Yukiyasu Kamitani, a neuroscientist at ATR Computational Neuroscience Laboratories in Kyoto.
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Dr. Allen R. Braun, who studies the neural basis of language at the National Institutes of Health, said the study was “an important first step to understanding visual imagery during sleep.” But he cautioned that the methods used by the Japanese team might not work for decoding dreams that occur during REM sleep, the stage characterized by rapid eye movement.
REM dreams — with their complex imagery, high emotional content and bizarre jumble of logic, time and space — largely remain a mystery. Decoding such dreams could unlock the secrets of many regions of the brain, not just the visual cortices that were monitored in the study.
“If you have a theory of the brain, you should be able to decode the brain,” Gallant said. The only limiting factors, he said, are “how well you can measure brain activity, how good your models are and how fast your computers are.”
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The fact that the computer models used data from waking minds and still made accurate predictions about dreams suggests the researchers are onto something about the links between waking and dreaming states, Gallant said.